Single-cell RNA-seq analysis of COs vs COiMG

UMAP

SCpubr::do_DotPlot(PV_filt,features=list('Microglia'=AB_markers_curated$Microglia),
                   group.by = "Organoids") + 
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1))

SCpubr::do_DotPlot(PV_filt, features=list('Epithelial'=AB_markers$`Epithelial Cells`,
                                             'Radial Glia'=AB_markers$`Radial Glia`,
                                             'NPCs'=AB_markers$NPCs,
                                          'Neurons'=AB_markers$Neurons,
                                          'Exc. neurons'=AB_markers$`Excitatory neurons`,
                                          'Inh. neurons'=AB_markers$`Inhibitory neurons`,
                                          'Interneurons'=AB_markers$Interneurons,
                                          'Cortical neurons'=AB_markers$`Cortical neurons`,
                                          'Mesenchymal'=AB_markers$`Mesenchymal cells`,
                                          'Oligodendrocytes'=AB_markers$Oligodendrocytes,
                                          'Astrocytes'=AB_markers$Astrocytes,
                                          'Microglia'=AB_markers$Microglia,
                                          'Cilia'=AB_markers$Cilia,
                                          'ChP'=AB_markers$ChP),
                   group.by = "seurat_clusters")+ 
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1))

Idents(PV_filt) <- PV_filt$seurat_clusters
identity <- c('0'='NPC',
              '1'='Cortical neurons',
              '2'='NPC',
              '3'='NPC',
              '4'='Mesenchymal/ChP (Cilia-associated)',
              '5'='NPC',
              '6'='Microglia',
              '7'='Microglia')
PV_filt <- RenameIdents(object = PV_filt, identity)
PV_filt@meta.data$identity <- Idents(PV_filt)
table(PV_filt$identity)
## 
##                                NPC                   Cortical neurons 
##                              79480                              22070 
## Mesenchymal/ChP (Cilia-associated)                          Microglia 
##                               5588                                282
PV_filt$identity <- factor(PV_filt$identity, levels=unique(PV_filt$identity))

DimPlot(PV_filt, reduction = 'umap', group.by='identity', cols = RColorBrewer::brewer.pal(7,'Accent')[c(1,2,3,6)])

DimPlot(PV_filt, reduction = 'umap', group.by='identity', split.by = 'Organoids', cols = RColorBrewer::brewer.pal(7,'Accent')[c(1,2,3,6)])

DimPlot(PV_filt, reduction = 'umap', group.by='identity', split.by = 'cell.line', cols = RColorBrewer::brewer.pal(7,'Accent')[c(1,2,3,6)])

table(PV_filt$cell.line,PV_filt$identity)
##        
##           NPC Mesenchymal/ChP (Cilia-associated) Cortical neurons Microglia
##   MSN38 38690                               2603            11712        26
##   WTC11 40790                               2985            10358       256
FeaturePlot(PV_filt,features = 'Cluster1',reduction = 'umap') + 
  scale_colour_gradientn(colours = rev(brewer.pal(n = 11, name = "RdBu"))) +
  ggtitle('Microglia markers')

FeaturePlot(PV_filt,features = 'Cluster2',reduction = 'umap') + 
  scale_colour_gradientn(colours = rev(brewer.pal(n = 11, name = "RdBu"))) +
  ggtitle('Mesenchymal/ChP markers')

FeaturePlot(PV_filt,features = 'Cluster3',reduction = 'umap') + 
  scale_colour_gradientn(colours = rev(brewer.pal(n = 11, name = "RdBu"))) +
  ggtitle('Neuron markers')

FeaturePlot(PV_filt,features = 'Cluster4',reduction = 'umap') + 
  scale_colour_gradientn(colours = rev(brewer.pal(n = 11, name = "RdBu"))) +
  ggtitle('NPC markers')

FeaturePlot(PV_filt,features = 'AIF1',reduction = 'umap') + 
  scale_colour_gradientn(colours = rev(brewer.pal(n = 11, name = "RdBu")))

FeaturePlot(PV_filt,features = 'TTR',reduction = 'umap') + 
  scale_colour_gradientn(colours = rev(brewer.pal(n = 11, name = "RdBu")))

FeaturePlot(PV_filt,features = 'STMN2',reduction = 'umap') + 
  scale_colour_gradientn(colours = rev(brewer.pal(n = 11, name = "RdBu")))

FeaturePlot(PV_filt,features = 'VIM',reduction = 'umap') + 
  scale_colour_gradientn(colours = rev(brewer.pal(n = 11, name = "RdBu")))

prop <- data.frame('CO'=prop.table(table(PV_filt$identity,PV_filt$Organoids)[,1]),'COiMg'=prop.table(table(PV_filt$identity,PV_filt$Organoids)[,2]))

df <- data.frame('Cell Type'=rep(rownames(prop),2),'Organoids'=c(rep('CO',4),rep('COiMg',4)),'Percentage'=round(c(prop[,1],prop[,2])*100,2))

ggplot(df, aes(x = Organoids, y = Percentage, fill = `Cell.Type`))+
  geom_bar(stat = "identity")+
  geom_text(aes(label = paste(Percentage,"%")), position = position_stack(vjust = 0.5)) +
  scale_fill_manual(values=RColorBrewer::brewer.pal(7,'Accent')[c(2,6,3,1)]) +
  theme_minimal()

SCpubr::do_DotPlot(PV_filt, features=list('Microglia'=AB_markers$Microglia,'Cilia'=AB_markers$Cilia,
                                          'ChP'=AB_markers$ChP),group.by = 'Organoids')+ 
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1))

SCpubr::do_DotPlot(PV_filt, features=list('COiMg DEGs'=coimg_degs[[2]][coimg_degs[[2]] %in% rownames(PV_filt)]),group.by = 'identity')+ 
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust=1))